Join a forward-thinking organization as a Data Engineer focused on critical datastore migration. You will be instrumental in moving data from on-premise Data Lakes to an AWS-hosted LakeHouse, a high-visibility project.

This role offers the opportunity to work with cutting-edge technologies and contribute to a significant digital transformation. If you are passionate about data and eager to innovate, we encourage you to apply.

Key responsibilities involve migrating extraction logic and job scheduling from legacy systems to the new LakeHouse environment. You will execute physical data transfers, ensuring complete data integrity.

Furthermore, you will translate and optimize legacy SQL and Spark-based consumption patterns for Snowflake and Iceberg, understanding usage patterns to deliver essential data products.

A rigorous approach to data validation and reconciliation is vital to confirm migrated data's functional equivalence. The role also requires an aptitude for learning new workflows and language constructs.

A Bachelor's or Master's degree in a quantitative field is required, alongside 3-5 years of hands-on coding experience in Python or Java. Professional proficiency in Python or Java is essential.

Deep familiarity with the full Software Development Life Cycle (SDLC), CI/CD best practices, and K8s deployment experience are necessary. You must demonstrate a sophisticated understanding of temporal data modeling, schema evolution, performance optimization, and architectural theory.

Expertise with technologies like Kafka, Spark, Snowflake, Apache Iceberg, and Hadoop (HDFS/Hive) is crucial for success in this role. Strong communication and collaboration skills are also key.